Tootfinder

Oil tanker damaged by blast weeks after visiting Russian ports, Bloomberg reports: https://benborges.xyz/2025/06/30/oil-tanker-damaged-by-blast.html

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation
Sanaa Khobizy
https://arxiv.org/abs/2506.22292 ht…

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation
In this paper, we extend the analysis of random Kronecker graphs to multi-dimensional networks represented as tensors, enabling a more detailed and nuanced understanding of complex network structures. We decompose the adjacency tensor of such networks into two components: a low-rank signal tensor that captures the essential network structure and a zero-mean noise tensor that accounts for random variations. Building on recent advancements in tensor decomposition and random tensor theory, we intr…

Läs den här texten av Elisabeth Åsbrink. "Varje dag tänker jag på Raphael Lemkins fråga om folkmord" https://www.dn.se/kultur/elisabeth-asbrink-varje-dag-tanker-jag-pa-raphael-lemkins-fraga-om-folkmord/

Elisabeth Åsbrink: Varje dag tänker jag på folkmord
Juristen Raphael Lemkin visste att folkmord har skett förr och därför kan det ske igen, skriver Elisabeth Åsbrink om dagens Gaza.

Running back D.J. Moore? Bears 'tinkering' with using veteran WR out of backfield

https://www.cbssports.com/nfl/news/running-back-d-j-moore-bear…

Classification of $\Lambda \neq 0$-vacuum algebraically special spacetimes with conformally flat $\mathscr I$ from Weyl tensor expansion
Marc Mars, Carlos Pe\'on-Nieto
https://arxiv.org/abs/2507.21292

Classification of $Λ\neq 0$-vacuum algebraically special spacetimes with conformally flat $\mathscr I$ from Weyl tensor expansion
We introduce a general algebraic decomposition of Riemann-like and Weyl-like tensors with respect to a non-null vector $u$. We derive Gauss, Codazzi and Ricci-type identities for the Weyl tensor, that allow to relate the components of the spacetime Weyl tensor with intrinsic quantities of the hypersurfaces orthogonal to $u$. Restricting to the case of $Λ$-vacuum spacetimes (with $Λ\neq 0$ and any dimension) admiting a conformal compactification, we then study the behaviour of the Weyl tenso…

Keyed Chaotic Tensor Transformations for Secure And Attributable Neural Inference
Peter David Fagan
https://arxiv.org/abs/2505.23655 https://

Keyed Chaotic Tensor Transformations for Secure And Attributable Neural Inference
This work introduces a novel framework for secure and privacy-preserving neural network inference based on keyed chaotic dynamical transformations. The proposed method applies a deterministic, cryptographically seeded chaotic system to tensors, producing non-invertible, user-specific transformations that enable authenticated inference, tensor-level watermarking, and data attribution. This framework offers a scalable and lightweight alternative to conventional cryptographic techniques, and estab…

Why are Dutch kids the world’s happiest? A teenager weighs in.
https://www.cnn.com/2025/06/29/health/dutch-kids-happiest-essay-wellness

Why are Dutch kids the world’s happiest? A teenager weighs in
Freedom for kids to move through the world on their own may be the key to the Netherlands’ top spot in childhood happiness.

Visual Analytics Using Tensor Unified Linear Comparative Analysis
Naoki Okami, Kazuki Miyake, Naohisa Sakamoto, Jorji Nonaka, Takanori Fujiwara
https://arxiv.org/abs/2507.19988 …

Visual Analytics Using Tensor Unified Linear Comparative Analysis
Comparing tensors and identifying their (dis)similar structures is fundamental in understanding the underlying phenomena for complex data. Tensor decomposition methods help analysts extract tensors' essential characteristics and aid in visual analytics for tensors. In contrast to dimensionality reduction (DR) methods designed only for analyzing a matrix (i.e., second-order tensor), existing tensor decomposition methods do not support flexible comparative analysis. To address this analysis limit…

Pauli Measurements Are Near-Optimal for Single-Qubit Tomography
Jayadev Acharya, Abhilash Dharmavarapu, Yuhan Liu, Nengkun Yu
https://arxiv.org/abs/2507.22001 https://

Pauli Measurements Are Near-Optimal for Single-Qubit Tomography
We provide the first non-trivial lower bounds for single-qubit tomography algorithms and show that at least $Ω\left(\frac{10^N}{\sqrt{N} \varepsilon^2}\right)$ copies are required to learn an $N$-qubit state $ρ\in\mathbb{C}^{d\times d},d=2^N$ to within $\varepsilon$ trace distance. Pauli measurements, the most commonly used single-qubit measurement scheme, have recently been shown to require at most $O\left(\frac{10^N}{\varepsilon^2}\right)$ copies for this problem. Combining these results, w…

An Image Noise Level Estimation Based on Tensor T-Product
Hanxin Liu, Yisheng Song
https://arxiv.org/abs/2507.20515 https://arxiv.org/pdf/2507.20515…

An Image Noise Level Estimation Based on Tensor T-Product
Currently, the noise level of color images is estimated by many algorithms through separate selection of each page of the third-order tensor using sliding blocks of size ${M_1} \times {M_1}$. The data structure of the tensor is disrupted by this method, leading to errors in the estimation results. In order not to disrupt the data structure of the tensor, we directly select the tensor using a sliding block of size ${M_1} \times {M_1} \times 3$ and then re-arrange it. The newly obtained tensor is…